1. Field of Invention
The present invention generally relates to a computer-implemented invention for producing publication layouts, and in particular, to a computer-implemented invention for optimizing publication layouts.
2. Description of Related Art
In the prior art, a publication layout is typically created with minimal computer support. Generally, computers are used to assist only in placing advertisements or editorials on a specific page. A number of problems are associated with such minimal support, including the inability to create an optimal relationship between advertisements and editorials, and the inability to maximize revenues.
An optimal relationship is established when a publication layout satisfies advertisers' requirements and produces the lowest possible printing costs. Typically, publishers spend a considerable amount of time evaluating both advertiser and editorial requirements, and determining the most cost-effective configuration. This detailed analysis involves generating several mock-ups or "dummys" of the layout creating different revenues and costs, before a final layout is produced. Printing deadlines prevent the publisher from creating all possible layouts and selecting the optimal arrangement. Consequently, publishers only review a designated number of layout configurations. Thus, the likelihood of one of these layouts resembling an optimum arrangement is small.
Furthermore, since publishers are limited to evaluating a small number of layouts, they lack the comparative information necessary to maximize revenue and minimize cost. In fact, without reviewing a large number of layouts, they can only speculate about whether a particular layout provides maximum revenue and/or minimum cost.
Thus, there is a need in the publishing industry for a comprehensive publication layout system that can resolve the above concerns.
One possible way of resolving the above concerns is to use biological programming models, such as a computer-implemented recombinant algorithm, a computer-implemented evolution algorithm, or a computer-implemented genetic algorithm, to optimize the selection of publication layouts. Such biological programming models are typically based on the concepts of natural selection and genetics, and are used to "breed" a population of program or data objects representing possible solutions. After many generations, one or more objects may emerge from the population that solves, or approximately solves, the problem at hand.
When applied to the problem of determining an optimal publication layout, biological programming models can be used to generate and evaluate a large number of possible layouts and then select among the generated layouts for the most optimal layouts, i.e., those layouts where the relationship between the placement of advertisements and editorials maximizes revenues and minimizes costs. The techniques for applying biological programming models to the determination of optimal publication layouts are described in more detail below.